「domain」の検索結果

Provide comprehensive techniques for attacking Microsoft Active Directory environments. Covers reconnaissance, credential harvesting, Kerberos attacks, lateral movement, privilege escalation, and domain dominance for red team operations and penetration testing.

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Advogado especialista em todas as areas do Direito brasileiro: familia, criminal, trabalhista, tributario, consumidor, imobiliario, empresarial, civil e constitucional.

日本語の概要は準備中です。原文の説明を表示しています。

Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.

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Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".

日本語の概要は準備中です。原文の説明を表示しています。

Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.

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Create or maintain a source-grounded kpopper knowledge model as a versioned plugin. Use when a reusable domain model should ship independently of any one project.

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Expert-level control systems engineering covering feedback control, PID design, root locus, frequency domain methods, state-space design, and digital control.

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Configure this repo for the engineering skills — set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering skills.

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Use when the user asks how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains.

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Fine-tune LLMs and VLMs using Unsloth on HF Jobs (Hugging Face on-demand cloud GPUs). Use when users want to fine-tune language models, train VLMs (Vision Language Models), do continued pretraining, domain adaptation, or run UV scripts on HF Jobs. Triggers on requests involving Unsloth training, HF Jobs GPU training, Qwen3-VL fine-tuning, Gemma VLM training, or LoRA fine-tuning on cloud GPUs.

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Design relational database schemas (and choose when to go NoSQL) that stay maintainable and fast. Use this skill whenever the user mentions tables, DDL, entities and relationships, normalization (1NF/2NF/3NF), primary and foreign keys, UUID vs bigint IDs, indexes (B-tree, composite, covering, partial), EXPLAIN, constraints (CHECK, UNIQUE, exclusion), transactions and isolation levels, migrations (Alembic, Prisma, Flyway, expand-contract, backfilling), or SQL vs NoSQL (MongoDB, DynamoDB, Cassandra, graph databases). Also trigger for "design the database", "model this domain", "which database should I use", or writing ORM models and migration files for PostgreSQL, MySQL, SQLite, or SQL Server.

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Use when setting up Traefik as a local reverse proxy — real domains on 127.0.0.1, trusted HTTPS via mkcert, automatic service discovery, and multi-project routing.

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Shared corpus-grounding engine — BM25 + structured filters + decision rules over CSV corpora via a domain manifest. Use when a skill needs grounded pre-action option-space constraints.

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Domine padrões comprovados de arquitetura backend incluindo Clean Architecture, Hexagonal Architecture e Domain-Driven Design para construir sistemas mantíveis, testáveis e escaláveis.

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Discover and install specialized agent skills from the open ecosystem. ALWAYS use this skill when the user asks 'how do I do X', 'find a skill for X', 'is there a skill for X', wants to extend agent capabilities, or needs help with a specific domain (design, testing, deployment, etc.). Make sure to use this skill whenever the user mentions skills, plugins, extensions, tools, or wants to find new capabilities for the agent. Integrates with the Skills CLI and skills.sh directory.

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[Documentation] Use when scanning the codebase to (re)generate ONE project-reference doc. Parameterized by `--target=<key>`: project-structure | backend-patterns | frontend-patterns | scss-styling | design-system | code-review-rules | domain-entities | feature-spec | docs-index | e2e-tests | integration-tests | seed-test-data | ui-system. Shared 4-phase scan engine; per-target detail lives in references/targets.md. `ui-system` is an orchestrator meta-target (`kind: orchestrator`) that runs the 3 UI child scans in parallel instead of the 4-phase engine.

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[Process] Use when the developer wants something explained or taught, or wants to know HOW TO REVIEW a change — by default the current working tasks + changes in context, or whatever the prompt names (a plan, a subsystem, a decision, a concept, a bug). AI derives WHAT to explain from the prompt and ALWAYS delivers a teacher-and-coach review guide, high level first then detail: what was done, a VISUAL MAP (system flowchart, domain ERD, sequence diagrams), the user stories and business rules with their REAL test-case IDs, a REVIEW PATH naming which files to open first and in what order with an exit criterion per stage, the technical concepts needed to follow it, how it works, why THIS solution, every alternative option with pros/cons, the trade-offs accepted, the blast radius, HOW TO TEST AND DEMO the change, the developer's decision levers, and written challenge prompts that provoke the reader to pressure-test the work. Works at ANY scope — from one line of code to the whole project: it SIZES the target into a scope tier, DECOMPOSES a large one into understanding groups, BREAKS the work into tasks before the first deep read, and ACCUMULATES the report group by group on disk so a huge explanation stays complete instead of thinning out. Writes the full report to a single combined markdown file (plans/reports/understand-*.md) that opens with a detailed summary section — or delivers it in full in chat when Step 3 finds no git-ignored directory for it — and always summarizes it in chat. Regardless of coding level. Never interrogates, never quizzes, never blocks.

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[Debugging] Use when analyzing or optimizing performance bottlenecks: database queries, N+1 fan-out, indexing, API latency, memory/GC, concurrency and pool saturation, algorithmic complexity (O(n²)), network/protocol round trips, frontend rendering and Core Web Vitals, caching, and distributed/resilience paths. Calibration constants and domain laws (latency ladder, Little's Law, utilization knee, CWV thresholds, symptom→cause triage) live in references/performance-knowledge.md.

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[Planning] Use when you need to start a new project from scratch with full waterfall inception — idea, research, domain modeling, tech stack, and implementation plan.

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Normalizes company names, industries, domains, locations, and descriptions. Use when the user provides company records and wants consistent canonical fields with confidence and unresolved items flagged.

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Chooses ecosystem-native release and changelog tooling (Changesets, Melos, release-plz) plus binary distribution (GitHub Release tarballs, install.sh) when the product is an executable. Use for release CI, install.sh, versioning, CHANGELOGs, shipping MCP/CLI without clone, or meta repos that only ship skills via npx skills—not domain app tutorials.

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Before improving anything, show the spread of what can concretely be done on this specific input — a short menu of 3-5 interventions from lightest to heaviest touch, then wait for the user to pick. Domain-agnostic; works on any material the user hands over. Trigger when the user says "spread", "show me my options", "what can you do with this", or asks to improve or fix something without specifying how. Do NOT trigger when the user has already named a specific fix — then just do the fix.

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Produce an up-to-date, state-of-the-art recommendation using domain expertise and brief web research. Use only when explicitly invoked.

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Create a new sub-agent definition file (agents/*.md) for the Claude Code plugin. Use this skill when the user wants to add a new specialized agent, define a new agent type, or create an agent that handles a specific domain of tasks. Trigger whenever the user mentions creating, adding, or defining a new agent or sub-agent.

日本語の概要は準備中です。原文の説明を表示しています。